Experimental Investigation of Residual Stress and its Impact on Machining in Hybrid Additive/Subtractive Manufacturing

Published

June 21, 2018

Author(s)

Jarred C. Heigel, Thien Q. Phan, Jason Fox, Thomas H. Gnaupel-Herold

Abstract

Hybrid Manufacturing leverages the advantages of both additive manufacturing (AM) with machining to create parts that have complex geometries, tight tolerances, and good surface finish. However, the residual stresses induced by both processes present a challenge. These high stresses can induce significant distortion that can damage the part during the additive process or lead to unanticipated distortion during the machining process. The current work investigates the impact of the residual stresses generated during the AM process on the part distortion during the subsequent machining operation. Powder bed fusion is used to create stainless steel cylinders and their geometries are measured before and after machining their outer diameter, allowing the resulting distortion to be calculated. The measured distortion is counter to what is expected from the distribution of the residual stress measurements made before the machining operation using neutron diffraction, suggesting that the machining imposes significant stresses that, in this case, counter-act the remaining stresses from the AM process and/or triggered a material phase change.

Proceedings Title

Proceedings of NAMRI/SME

Issue

26

Conference Dates

June 18-22, 2018

Conference Location

College Station, TX, US

Conference Title

46th SME North American Manufacturing Research Conference, NAMRC 46

Pub Type

Conferences

Download Paper

https://doi.org/10.1016/j.promfg.2018.07.120

Local Download

Keywords

Hybrid manufacturing, additive manufacturing, residual stress, distortion

Citation

Heigel, J. , Phan, T. , Fox, J. and Gnaupel-Herold, T. (2018), Experimental Investigation of Residual Stress and its Impact on Machining in Hybrid Additive/Subtractive Manufacturing, Proceedings of NAMRI/SME, College Station, TX, US, [online], https://doi.org/10.1016/j.promfg.2018.07.120, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=924962 (Accessed September 12, 2024)